The capacitated pollution routing problem with pickup and delivery in the last mile

Abstract

Purpose With the increasing awareness of global warming and the important role of last mile distribution in logistics activities, the purpose of this paper is to build an environmental and effective last mile distribution model considering fuel consumption and greenhouse gas emission, vehicle capacity and two practical delivery service options: home delivery (HD) and pickup site service (PS). This paper calls the problem as the capacitated pollution-routing problem with pickup and delivery (CPRPPD). The goal is to find an optimal route to minimize operational and environmental costs, as well as a set of optimal speeds over each arc, while respecting capacity constraints of vehicles and pickup sites. Design/methodology/approach To solve this problem, this research proposes a two-phase heuristic algorithm by combining a hybrid ant colony optimization (HACO) in the first stage and a multiple population genetic algorithm in the second stage. First, the HACO is presented to find the minimal route solution and reduce distribution cost based on optimizing the speed over each arc. Findings To verify the proposed CPRPPD model and algorithm, a real-world instance is conducted. Comparing with the scenario including HD service only, the scenario including both HD and PS option is more economical, which indicates that the CPRPPD model is more efficient. Besides, the results of speed optimization are significantly better than before. Practical implications The developed CPRPPD model not only minimizes delivery time and reduces the total emission cost, but also helps logistics enterprises to establish a more complete distribution system and increases customer satisfaction. The model and algorithm of this paper provide optimal support for the actual distribution activities of logistics enterprises in low-carbon environment, and also provide reference for the government to formulate energy-saving and emission reduction policies. Originality/value This paper provides a great space for the improvement of carbon emissions in the last mile distribution. The results show that the distribution arrangement including HD and PS services in the last mile adopting speed optimization can significantly reduce the carbon emission. Additionally, an integrated real-world instance is applied in this paper to illustrate the validity of the model and the effectiveness of this method.

Environmental and social implications of incorporating carpooling service on a customized bus system

“…Since the introduction of the AS by Dorigo et al (1991aDorigo et al ( , 1991bDorigo et al ( , 1996 and Colorni et al (1992aColorni et al ( , 1992b, the algorithm has been employed in different NP-hard combinatorial optimization problems such as activity crashing in project management (Abdallah et al, 2009), the car sequencing problems (Moya et al, 2019;Sun and Fan, 2017), the vehicle routing problems (Kim and Park, 2018;Tan et al, 2019;Liu et al, 2020), the job shop scheduling problems (Jong et al, 2020), resource allocation problems (Chaharsooghi and Kermani, 2008) and the travelling salesman problems (López-Ibáñez and Blum, 2010;Ebadinezhad, 2020). It has been shown ACO outperforms other heuristics like genetic algorithm and simulated annealing on a number of problems.…”

The Development of Sustainable Transportation For E-Grocery

“…Kellner (2016) analyzed the impact of traffic congestion on CO2 emission, but did not consider the impact on food quality (Kellner 2016). Tan et al (2019) proposed pollution routing algorithm designed for last-mile deliveries to reduce negative influence on the environment (Tan et al 2019). Another research conducted by Velázquez-Martínez et al ( 2016) included altitude, cargo weight and truck power when optimizing routes based on CO2 levels (Velázquez-Martínez et al 2016).…”

Estimating CO2 emissions from emergency-supply transport: The case of COVID-19 vaccine global air transport

“…When evaluating FLM, it is important to examine what is being transported - whether it is passengers or commodities ( Nocera et al, 2019 ). For freight transport, the home delivery (HD) in the last mile is normally considered the most complex ( Nocera et al, 2019 ) and CO 2 intensive section of a transportation journey ( Tan et al, 2019 ). Keeping this in mind, innovative approaches like the usage of drones (autonomous unmanned aerial vehicles) to reduce the freight sector's last-mile CO 2 releases are discussed in the related literature ( Elsayed and Mohamed, 2020 ).…”